Guanfeng Wu, Qingshan Chen, Feng Cao, Yang Xu, Xiaomei Zhong
{"title":"Parallel hybrid genetic algorithm for sat problems based on OpenMP","authors":"Guanfeng Wu, Qingshan Chen, Feng Cao, Yang Xu, Xiaomei Zhong","doi":"10.1109/ISKE.2017.8258783","DOIUrl":null,"url":null,"abstract":"SAT problem is the first proved NP-complete problems. Heuristic methods on solving the SAT problem although belongs to incomplete method, but it has its advantages. Genetic Algorithm (GA) as one of the heuristic algorithms, was applied to solve the SAT problem of many years, and also got some better results combine with other algorithms. However, there is still room for improvement. In this paper we combine GA with the Local Search Algorithm (LSA) and improve the sort algorithm. Using the Open MP to implement the Parallel Hybrid GA based on the Coarse-Grained Model (CGPHGA). This article describes the design and implementation of CGPHGA in detail, According to the experimental results, CGPHGA improves the success rate and efficiency.","PeriodicalId":208009,"journal":{"name":"2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISKE.2017.8258783","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
SAT problem is the first proved NP-complete problems. Heuristic methods on solving the SAT problem although belongs to incomplete method, but it has its advantages. Genetic Algorithm (GA) as one of the heuristic algorithms, was applied to solve the SAT problem of many years, and also got some better results combine with other algorithms. However, there is still room for improvement. In this paper we combine GA with the Local Search Algorithm (LSA) and improve the sort algorithm. Using the Open MP to implement the Parallel Hybrid GA based on the Coarse-Grained Model (CGPHGA). This article describes the design and implementation of CGPHGA in detail, According to the experimental results, CGPHGA improves the success rate and efficiency.